In collaboration with Merrick Howarth
Here at Stanford, my primary academic focus is on sustainable urban systems, where I learn data-driven approaches and use systems and equity rooted thinking to improve cities. In a sense, thinking about what a “complete community” is. In this assignment, I’m given the opportunity to think about what an ideal community looks like, design a way to measure it, and apply that measure to a real community here in the Bay Area. The report below describes a methodology for evaluating a community for completeness and applying it to West Oakland.
We define completeness in this report as access to essential amenities that promote wellbeing. We define access as the freedom to reach such amenities within a reasonable amount of time using any transportation mode.
West Oakland is a neighborhood west of Downtown Oakland, with a documented history with environmental racism. From its proximity to several highway networks which contributed to air pollution issues, we determined West Oakland would be an interesting community to apply our complete communities methodology. We first pulled block groups in Oakland then filtered by visual inspection the block groups that make up West Oakland. In the map below, you’ll notice that this community is bounded by highways on all four sides.
The first step is to identity those essential amenities, which we’ll call “places of interest” according to OpenStreetMaps. We believe that a complete community has access to healthy food, green spaces, community centers, educational institutions, and transit within 15 of walking, cycling, and driving.
## amenity amenity_value amenity_quantity amenity_decay
## 1 community_centre 0.80 1 0.6931472
## 2 convenience 0.65 3 0.2310491
## 3 fast_food -0.75 5 0.1386294
## 4 supermarket 1.00 2 0.3465736
## 5 park 0.85 3 0.2310491
## 6 green_grocer 1.00 2 0.3465736
## 7 playground 0.80 5 0.1386294
## 8 kindergarten 0.85 3 0.2310491
## 9 school 0.90 2 0.3465736
## 10 transit_stop 0.95 4 0.1732868
## 11 library 0.75 2 0.3465736
## mode mode_value mode_reasonable mode_decay
## 1 walking 1.00 15 0.04620981
## 2 cycling 0.85 15 0.04620981
## 3 driving 0.60 15 0.04620981
The two data frames show you the selected amenities, how I valued them (on a scale from -1 to 1), how many an ideal community has access to in those 15 mins. You’ll note that “fast food” is given a negative value. This is because we want to define locations that provide healthy food; so even if people in said community have access to food, if it’s not healthy, it actually hurts it. In the mode data frame we identify the three transportation modes, which also a value ranking with walking receiving a full score and driving receiving the lowest score. This is because we want our complete communities to discourage driving. Finally with both data frames, you’ll find a decay tab that calculates the rate at which an amenities value decreases, with the threshold being the number of such amenities in a community. This is based on an accessibility analysis methodology developed by New Zealand researchers.
You can get a sense of scale by visualizing these POIs across California in the map below:
One last important component to keep in mind: since access to healthy food is essential to our complete community, we flagged supermarkets as critical amenities; the largest assumption from this is that all supermarkets have access to fresh produce.
The next key element central to analyzing completeness is/are isochrones, which measure travel distance from a central point. I use isochrones to determine how many of those POIs are within 5, 10, and 15 mins of walking, biking, and driving. The maps below show first, a five minute walking isochrone and second, a 15 minute driving isochrone in West Oakland.